В европейской стране бизнесмен украсил город флагами и получил огромный штрафБританского бизнесмена оштрафовали за украшение города государственными флагами
As a data scientist, I’ve been frustrated that there haven’t been any impactful new Python data science tools released in the past few years other than polars. Unsurprisingly, research into AI and LLMs has subsumed traditional DS research, where developments such as text embeddings have had extremely valuable gains for typical data science natural language processing tasks. The traditional machine learning algorithms are still valuable, but no one has invented Gradient Boosted Decision Trees 2: Electric Boogaloo. Additionally, as a data scientist in San Francisco I am legally required to use a MacBook, but there haven’t been data science utilities that actually use the GPU in an Apple Silicon MacBook as they don’t support its Metal API; data science tooling is exclusively in CUDA for NVIDIA GPUs. What if agents could now port these algorithms to a) run on Rust with Python bindings for its speed benefits and b) run on GPUs without complex dependencies?
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Obviously an API scraper and data viewer alone do not justify an OPUS 4.5 CHANGES EVERYTHING declaration on social media, but it’s enough to be less cynical and more optimistic about agentic coding. It’s an invitation to continue creating more difficult tasks for Opus 4.5 to solve. From this point going forward, I will also switch to the terminal Claude Code, since my pipeline is simple enough and doesn’t warrant a UI or other shenanigans.，推荐阅读heLLoword翻译官方下载获取更多信息